SCOAP3 Repository 4 records found  Search took 0.02 seconds. 
1. Machine learning uncertainties with adversarial neural networks / Englert, Christoph ; Galler, Peter ; Harris, Philip ; Spannowsky, Michael
Machine Learning is a powerful tool to reveal and exploit correlations in a multi-dimensional parameter space. [...]
Published in EPJC 79 (2019) 4 10.1140/epjc/s10052-018-6511-8
Fulltext: Download fulltextXML Download fulltextPDF (PDFA);
2. Fractal based observables to probe jet substructure of quarks and gluons / Davighi, Joe ; Harris, Philip
New jet observables are defined which characterize both fractal and scale-dependent contributions to the distribution of hadrons in a jet. [...]
Published in EPJC 78 (2018) 334 10.1140/epjc/s10052-018-5819-8
Fulltext: Download fulltextXML Download fulltextPDF (PDFA);
3. Thinking outside the ROCs: Designing Decorrelated Taggers (DDT) for jet substructure / Dolen, James ; Harris, Philip ; Marzani, Simone ; Rappoccio, Salvatore ; et al
We explore the scale-dependence and correlations of jet substructure observables to improve upon existing techniques in the identification of highly Lorentz-boosted objects. [...]
Published in JHEP 1605 (2016) 156 10.1007/JHEP05(2016)156 arXiv:1603.00027
Fulltext: Download fulltextXML Download fulltextPDF (PDFA);
4. Pileup per particle identification / Bertolini, Daniele ; Harris, Philip ; Low, Matthew ; Tran, Nhan
We propose a new method for pileup mitigation by implementing “pileup per particle identification” (PUPPI). [...]
Published in JHEP 1410 (2014) 059 10.1007/JHEP10(2014)059 arXiv:1407.6013
Fulltext: Download fulltextXML Download fulltextPDF (PDFA);

See also: similar author names
430 Harris, P.
1 Harris, P.G.
Interested in being notified about new results for this query?
Subscribe to the RSS feed.